Early Look: AeroLab Tech’s Aerodynamic Sensors

For years, aerodynamic sensors and testing facilities for cycling have been appropriated to not just the pointy end of the pack, but the absolute tip of that pointy end.  The cost for a mere hour of wind tunnel time is as much as a power meter, and that excludes the travel costs required to get to but a handful of centers around the world – or that they recommend two hours of time. Even in the most time-optimized test setup, iterations in a wind tunnel take lots of time.

Born out of those limitations (among others), we saw new facilities like the ERO Sports one (and others driven by Alphamantis Technologies, which Garmin recently acquired).  This service leveraged velodromes, which had an advantage of putting a cyclist on a moving bike, versus just a static wind tunnel.  The last option on the table was using a bit of software and careful data collection in set procedures.  This method being called Virtual Elevation (also called the Chung method, after its creator – Robert Chung). Virtual Elevation has other uses beyond just aerodynamics, such as looking at power meter accuracy too.  But the vast majority of the iron-distance field would find it too complex to approach.

And one of the biggest challenges of all of these solutions is the inability to move it to race day or training days.  They were largely for one-off testing days, or something you’d analyze from a desk at home.

And that’s where AeroLab aims to fill that gap.  They’ve got a device that gives you real-time information out on the bike during your ride.  Mind you, AeroLab is hardly the only company we’ll see put forth products and services in 2018 in this category.  I talked about this a bit within my Symposium Keynote this past fall.  There’s also Notio (which I’ve tried briefly too), as well as Swiss Side, and Red is Faster.  Then whatever Garmin is doing with their acquisition of Alphamantis, and finally, the others that haven’t made themselves public yet.  And all of these companies seem to have their sights on 2018 product introductions.  Oh, and to be totally complete here – we saw the Velocomp Newton do real-time CDA back years ago, though the head unit didn’t really compete with others on the market.

A Look At The Tech:

Ironically enough, it was on my way to the ANT+ Symposium this past fall to give that very keynote that I got a chance to test ride the AeroLab system.  I carefully followed Google Maps in my rental car to what was literally described to me via text message as the middle of nowhere. And it was.  I had successfully navigated to a locked gate on a cattle farm, aside a perfectly straight road.

A few minutes later the guys from Energy Lab Sports showed up, and escorted me a bit further to our starting location for the day.  It was here they had a bike waiting for me, with a power meter already affixed.  Also already affixed was their aerodynamic sensor and a funky looking bike computer of sorts.

In reality, it was more of a beta testing display device. Like most of these companies, they intend to let you leverage your existing bike computer, largely through the use of Garmin Connect IQ or other arrangements with head unit makers.  The company has joined others in trying to establish an ANT+ technical working group to standardize some of the data streams here, so that all head unit and aerodynamic sensors can work from the same sheet of music (like it is today for things like heart rate sensors or power meters).

It’s that pointy looking aerodynamic sensor though where the majority of the magic is.  The pointy thing is a multi-hole pitot probe.  That’s what’s capturing wind speed and direction. Inside the larger housing is a host of hardware designed to capture and display the following metrics:

A) Wind Speed
B) Wind Angle
C) Wind Gust Magnitude
D) Coefficient of Aerodynamic Drag (CdA)
E) Coefficient of Rolling Resistance (Crr)
F) Humidity
G) Air density

Atop those metrics that are more ‘capture-based’, they’ve added another pile of metrics that are more calculation based, which are noted below.

H) Current power to overcome drag
I) Current power to overcome the road slope
J) Current power of acceleration
K) Current power to overcome rolling resistance
L) Estimated drivetrain power loses

The entire suite also contains an accelerometer, gyroscope, temperature sensor, humidity sensor, and barometric altimeter.  It also supports connecting to ANT+ sensors too.  All of this data is recorded at a rate of 2Hz, 5Hz, or a 10Hz (user selectable).  That means it’s captured at 2, 5, and 10 times a second.

Without going too far into the weeds, the data in this prototype was recorded onto a MicroSD card, but by time production hits it’ll be wirelessly transferred to a planned online platform.  The data is written as a CSV file, which they say they’ll have guidance for importing into Excel, MATLAB, and Golden Cheetah.  Below is a sample from the data file with the headers removed:

The battery life of the platform is quite reasonable.  At a 2Hz data storage rate, you’re looking at about 25 hours.  Whereas at a 10Hz data rate, you’re looking at about 5 hours.  So more than your bike computer would last in the lesser recording mode, but about what the more competitive iron-distance athletes would need in the highest recording rate to finish an Ironman (possibly a tiny bit short).  But again, most training/racing circumstances wouldn’t really require the highest recording rates.

When it comes to setup, it’s desirable to use either an ANT+ or Bluetooth Smart wheel speed sensor for the most accurate recording, though the platform can fall back on GPS for ground speed measurement.

Finally, note that the company intends to offer two different variants of their product.  One is a consumer version and one is a coaching version.  The consumer one aims to have core measurements like real-time CdA, wind, and wind yaw.  As well as the ability to run your specific bike/person setup through a course simulator. Whereas the coaching one would add in features like body position sensors and potentially those measuring sweat rate.

A Test Ride and Data:

The single biggest reason a product like AeroLab exists is because when you go and test in a wind tunnel or other aero facility, you quickly realize that slightly more aerodynamic body position changes are in many cases the difference between having your finger a mere centimeter in one direction or another (or possibly even less drastic than that).  The challenge then becomes how to memorize that position after just a few minutes in, say, February, and transfer that all the way to your ‘A’ race in August.

With a road-capable system that you can use day in and day out, you can figure out that ideal position and adjust accordingly.

The first step in doing a ride with the unit is getting the sensor mounted to the bike, which is done using a fairly universal GoPro mount adapter. The extra Christmas lights wiring won’t be there on final production units of course, it’s a prototype.  The final variants will be wireless. Also, the Cervelo markings were mostly due to some early interest there from Cervelo.

After which, you’ll do a short calibration procedure leaving the bike in a level spot sheltered from the wind for about 30 seconds.  Upon completion, you’re ready to roll.

In my case, we would do two 10KM loops around a perfectly square set of farm roads on the outskirts of Calgary.  Here you can see the Strava file:

Don’t worry though, you don’t need to ride in squares. It just helped to validate some aspects of the test data set from them.

In my test, we had a team car accompanying us (primarily to walk me through a series of ‘interesting’ tests, but also to take some photos with my camera).  Additionally, the team car acted as a safety car so that we could so some of the intersections without braking, since that would impact the aerodynamic results, as it wouldn’t account for braking and would have assumed my aero position went all upside-down.

 

For the majority of the first loop, I just got used to riding with the display of the system.  In particular, using some slightly different metrics.  Sure, I was familiar with CdA and Crr and the display of that value – but there were other metrics to evaluate here including Paer – which is the power to overcome my aerodynamic drag.  The goal here being to keep this number as low as possible.  If I were to sit up, that power would increase, since it would now take more power to overcome that aerodynamic drag.

In addition to the power to overcome aerodynamic drag, they’re also looking at aspects like the power to overcome road slope, and power to overcome rolling resistance.  With the general principals the same there.

You’ll notice above the balance metric (top one) on the Garmin looks a bit funny.  Usually this would be split something like 48%-52%.  But in this case, what’s actually happening is that their system is re-broadcasting as a power meter.  So in reality, they connect directly to your ANT+ power meter, and you can connect to it as a power meter.  From there they ‘took over’ the balance field to show CdA.  Of course, the plan by production is just to make that a Connect IQ data field.  But this is basically akin to what we’ve seen companies like Stryd do pre-CIQ.

Here’s a look at some of these numbers for my first loop (solo):

As you can see in the charts above, my CdA for much of this loop was about .30-.40.

In some cases it climbed a bit, likely in places where I briefly got out of aero or otherwise changed position (such as up some small climbs).  Note that this was a loaned bike that I had no specialty fit for, nor was I wearing particularly aero clothing.  The purpose of this ride wasn’t to find my perfect aerodynamic position – rather, it was just to show how the tech worked.

One can start to overlay these different metrics together to see where the inputs and outputs of the entire system fit together.  This is my first loop, which again, was solo (thus, no draft effect).

On the second loop we started playing with the impacts of drafting on the sensors.  To assist with this, another rider, Robert, was riding either in front or behind me.

We alternated positions throughout the second 10KM loop, and I was able to see the impact on things.  During the first portion of this loop where I trailed Robert, my CdA  skyrockets.

This is because there’s very little direct wind hitting the sensor, thus the wind sensor is no longer measuring my true wind speed, but rather the perceived wind speed.

You can see this shift again when I pass Robert.  At that point his CdA spikes, and mine normalizes:

However, it gets slightly more interesting as we both slow down to climb a short hill towards the end of the loop.  It’s at that point that you can see that the draft impact is lessened, since the overall wind speed is lessened.

To put things into a bit of audio-visual context, the AeroLab crew showed me this brief animated graph as part of a larger slide deck.  They explain over the course of 90 seconds what’s going on with real-time CdA at different points during the ride.  The video recording is super basic, so I’m just uploading it as-is for those that are curious.

Of course, all of this is very basic in terms of what I highlighted above.  And more importantly, to some degree it’s not 100% verifiable.  However, a lot can be backed up by cross-referencing it against other methods, like the Chung method.  The company did that for my ride (specifically Lap 1, which was ‘clean’ and free from all the draft testing we did on Lap 2), and was able to note some of the challenges that non-real-time methods face around assumptions.  With AeroLab, it’s able to eliminate assumptions through its larger slate of sensors. Versus software-only options lacking those sensors have to make educated guesses.

Which isn’t to say that those guesses are bad, but they just aren’t as accurate as measured values.  One is free, one might be upwards of $1,000. Both have value.

Also, it should be noted that the AeroLab system isn’t perfect either.  For example, there are some minor increases in CdA towards the end of the loop that can’t fully be explained.  Perhaps it’s the terrain (a climb), combined with other environmental factors, or perhaps it’s passing cars impacting the wind around us.  All of which are areas that will no doubt need more detailing for not just AeroLab but other platforms as on-bike aerodynamic sensors become more widespread.

(Note: AeroLab did provide me a full and detailed whitepaper of the session with boatloads of data and extensive explanations of what was going on during each part. They’re going to make that public in the next 3-4 weeks, so once they do I’ll link to it here.)

Going Forward:

All of the companies mentioned at the start of this post are vying for the first to market title, but the long-term winner will be the one who can put together an affordably accurate system that’s easy to use and unscrewupable.  It may sound silly, but one of the biggest challenges of aerodynamic testing today is the complexities to get the system setup and producing accurate numbers.  AeroLab has done a fair bit there to try and address that within their prototypes, though, I suspect there’s still a bit more work to be done.

The main challenge that AeroLab will face is how to better integrate with head units.  Most consumers of the platform would likely prefer to use their own head unit.  The company acknowledges that and notes that they won’t require using their display, which is good news.  It’s effectively the same challenge that ProShift faced, and to a lesser extent what Velocomp faced with Newton.  And we see Notio with their system is focusing on as well, by just delivering the data via Garmin Connect IQ data fields, so users can get the data fields they want without the display they don’t.

The good news is shifting that data display is relatively trivial in the grand scheme of things – since they’ve demo’d it already with an Edge 520 for certain fields.  Hopefully that’ll be the final direction going forward – if so, I think they’ll have a plethora of suitors, assuming the price is right.

Speaking of which, that is the final outstanding question – what will the price be?  None of the companies have listed final prices, though competitor Notio noted they intend to offer roughly three levels, with prices spanning likely in the $500-$800 range for the mid-tier offering that includes real-time CDA and some level of aero guidance.  AeroLab says that they’ll be “well under $1,000” for a consumer version, and about $1,800 for a coaching variant.

As for AeroLab, the company notes that they expect to start their beta program in the next few months.  Though they say you can sign-up for it now, should you want to put your name in the hat for getting their aerodynamically beta bits.

With that, thanks for reading!

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